class_docstr: Responsible for generating samples of the leaf node predictions
  Essentially just draws from a normal distribution with prior specified by model parameters
  
  Uses a cache of draws from a normal(0, 1) distribution to improve sampling performance
code: def __init__(self, scalar_sampler=NormalScalarSampler(60000)):
      self._scalar_sampler = scalar_sampler
  
file_path: imodels/imodels/experimental/bartpy/samplers/leafnode.py
imports: import numpy
  from ..model import Model
  from ..node import LeafNode
  from ..samplers.sampler import Sampler
  from ..samplers.scalar import NormalScalarSampler
label_desc: Use image node_id 1 to create a new LeafNodeSampler object from inherited base classes: Sampler with example: obj = LeafNodeSampler(scalar_sampler)